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Fifth Generation (5G) wireless systems are expected to connect an avalanche of “smart” objects disseminated from the largest “Smart City” to the smallest “Smart Home”. In this vision, Long Term Evolution-Advanced (LTE-A) is deemed to play a fundamental role in the Internet of Things (IoT) arena providing a large coherent infrastructure and a wide wireless connectivity to the devices. However, since LTE-A was originally designed to support high data rates and large data size, novel solutions are required to enable an efficient use of radio resources to convey small data packets typically exchanged by IoT applications in “smart” environments. On the other hand, the typically high energy consumption required by cellular communications is a serious obstacle to large scale IoT deployments under cellular connectivity as in the case of Smart City scenarios. Network-assisted Device-to-Device (D2D) communications are considered as a viable solution to reduce the energy consumption for the devices. The particular approach presented in this paper consists in appointing one of the IoT smart devices as a collector of all data from a cluster of objects using D2D links, thus acting as an aggregator toward the eNodeB. By smartly adapting the Modulation and Coding Scheme (MCS) on the communication links, we will show it is possible to maximize the radio resource utilization as a function of the total amount of data to be sent. A further benefit that we will highlight is the possibility to reduce the transmission power when a more robust MCS is adopted. A comprehensive performance evaluation in a wide set of scenarios will testify the achievable gains in terms of energy efficiency and resource utilization in the envisaged D2D-based IoT data collection.

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Multimedia content delivery over satellite systems is considered as a promising service in emerging 5G networks. The aim of this paper is to design a novel radio resource management algorithm for efficiently managing multicast multimedia content transmission over satellite network. The proposed approach performs the spectrum management on a per-group basis, by splitting multicast terminals into different subgroups according to the experienced channel qualities. We demonstrate that subgrouping policy defined by the authors as multicast subgrouping-maximum satisfaction index (MS-MSI), based on a new metric (i.e., MSI), overcomes the weakness of the previous techniques proposed in the literature and provides the best tradeoff between user throughput and fairness. As a further result, we demonstrate that MS-MSI is robust to the long propagation delay of satellite links. An extensive simulation campaign has been conducted by considering several satellite environments

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